基于多因子协同放大的可能最大暴雨估算

Estimation of Probable Maximum Precipitation Based on Multi-factor Cooperative Amplification

全球变暖影响下可能最大暴雨(PMP)估算是水文气象学领域的研究难点。以怒江上游为例,提出了一种考虑温度变化的三因子(水汽、动力、温度)协同放大的PMP估算方法,该方法主要以数值天气模式(WRF)的物理因子扰动试验为基础,首先进行因子三要素(水平范围、垂直层数和放大倍比)的数值扰动试验,明晰单个因子变化对降雨的影响,然后进行两两因子同时变化的扰动试验,定量描述因子协同作用与暴雨量之间的驱动—响应关系,从而确定能够产生最大降水的最不利情景以估算PMP。该方法在多因子协同放大的数值试验基础上,将温度因子变化引入PMP估算中,物理性较强。

Estimation of possible maximum precipitation(PMP)under the influence of global warming is difficult in the field of hydrometeorology.Therefore,a PMP estimation method considering the cooperative amplification of three factors(water vapor,power and temperature)with temperature change was proposed by taking the upper reaches of the Nujiang River as an example.This method is mainly based on the physical factor disturbance test of numerical weather model(WRF).Firstly,the numerical disturbance test of three factors(horizontal range,vertical layers and magnification ratio)is carried out to clarify the impact of single factor change on rainfall.And then the disturbance test of pairwise factors synchronously change is carried out to quantitatively describe the driving response relationship between the synergy of three factors and rainstorm,so as to determine the most unfavorable scenario that can produce maximum precipitation to estimate PMP.Based on the numerical experiment of multi-factor cooperative amplification,this method introduces the change of temperature factor into the estimation of PMP,which has better physical property.